Implementing Memory in Our Agent › When to Use What
Michael BrenndoerferJuly 5, 20251 min read
AI Agent HandbookAll chapters Part 6 of 15Memory and Retrieval - How Agents Remember
Implementing Memory in Our Agent › When to Use WhatOne section · Sections in this chapter7 / 13 ↓
Sections in this chapter13
Here's a practical guide for choosing memory strategies:
For personal projects or prototypes:
- Use the simple JSON-based approach we've shown
- Sliding window for conversation history
- Local embeddings for semantic search
For production applications with <1000 users:
- SQLite or PostgreSQL for knowledge storage
- Consider Redis for conversation history (fast, ephemeral)
- Still use local embeddings if cost is a concern
For large-scale applications:
- Vector database (Pinecone, Weaviate, Chroma) for knowledge
- Redis or similar for conversation state
- API-based embeddings for best quality
- Implement proper user isolation and security